This is a course on building your own stock and cryptocurrency automated trading programs using ChatGPT, even without prior coding knowledge. You will gain both AI development skills and financial investment knowledge through hands-on practice covering the entire process, from data collection to predictive model development, stock recommendation systems, and actual automated trading.

We will study AX (AI Transformation) strategies that go beyond simply utilizing AI tools to fundamentally redesign an organization's work processes and decision-making systems. We will analyze AI transformation cases from global companies across various industries, such as retail, finance, and healthcare, and establish actionable strategies and roadmaps applicable to our organization.

This course analyzes the US-China currency hegemony competition, centered on dollar-based stablecoins and China's digital yuan. By systematically studying how changes in the global financial order in the digital currency era affect the domestic economy, financial markets, and individual asset strategies, it provides insights that can be immediately applied to practical work.

Learn the basics of visual thinking, a technique for quickly organizing complex information using text and drawings. From ideation to utilizing digital mind maps (Xmind), you will master practical thought-organization know-how step-by-step to enhance work productivity. Start as easily as learning a language and complete your visual thinking skills that can be applied immediately to daily life and work.

Understand the essence of data visualization as a balance between scientific accuracy and aesthetic expression, and systematically learn everything from color and symbology principles to graph design. By utilizing visual attributes based on cognitive science principles, you will complete your data communication skills to achieve reliability and persuasiveness in professional practice.

Learn the smart work mindset and practical skills needed to survive in a rapidly changing business environment. This course comprehensively covers essential work skills for modern professionals, ranging from how to use the latest productivity tools like ChatGPT and Notion to creative and logical thinking, time management, and leadership.

Learn the core concepts and operating principles of Physical AI, which moves beyond the screen to be implemented in robots, autonomous vehicles, and drones. Understand the sensing-perception-action mechanism, digital twin-based learning, and the importance of embodied data, while exploring the global technological competition and Korea's strategic direction through real-world cases in industries such as manufacturing, mobility, and agriculture.

Together with Professor Soon-chil Lee, South Korea's leading authority on quantum computing, you will systematically learn everything from the core principles of quantum technology to its business impact. Through the basic concepts of quantum mechanics, the operating principles of quantum computers, and industrial application cases, you will complete your quantum literacy to preemptively understand future technological changes and establish strategies.

Systematically learn the internal structure and operating principles of Apache Kafka, a core technology for real-time data streaming. From basic concepts to cluster construction, client development, and microservices application, you will acquire all the practical knowledge and know-how necessary to build the capability for stable Kafka operations.

We will examine the changes that AI technology has brought to the entire financial industry through various cases such as fintech, investment, credit risk, and fraud detection. Through hands-on practice using Python libraries, you will understand the application methods and strategic insights of financial AI and learn how to safely integrate generative AI into financial services.

Starting from installing MariaDB and understanding its structure, you will learn step-by-step from writing SQL queries and utilizing functions to joins and subqueries. You will master core practical features such as table design, performance management, backup, and recovery through hands-on practice, completing the practical skills necessary for database development and operation.

This is a practical clean code writing course for developers who have completed the basics of Python. You will learn specific methodologies for writing highly readable and maintainable code, and develop coding skills that can be immediately applied to real-world projects through the know-how of professional programmers.

Systematically learn Docker, a core tool for container-based application deployment, from the basics to practical application. Starting with Docker's basic structure and commands, you will develop practical skills that can be immediately applied to real-world tasks, including container packaging in microservices architecture environments, deployment automation, and standardization of production environments.

Learn how to develop cloud-native applications using Kubernetes, the standard for container orchestration. From core Kubernetes concepts to actual application deployment and operations automation, you can acquire practical skills that are immediately applicable in the field. Learn how to build efficient resource management and deployment processes by integrating development and production environments.

This is a process of developing a practical web service in collaboration with AI agents based on TARS prompt engineering principles. You will gain full-stack development experience covering everything from UI/UX component creation to CRUD functions, API integration, and data visualization, ultimately completing your own idea as a viable MVP.

In an era where flexible data processing beyond the limits of SQL is required, learn everything about MongoDB. From NoSQL concepts to installation, CRUD practice, aggregation pipelines, text search, and indexing, you will learn step-by-step and complete your practical skills through Python crawling integration and container environment construction.

In the era of AI and Big Data, are you utilizing your organization's data effectively? This course builds essential capabilities for reading and interpreting data, covering everything from the foundations of statistical thinking to the core principles of machine learning and deep learning. Grow into a practical leader capable of discovering patterns amidst volatility and making data-driven decisions.

This course is designed for those who are new to React, an essential skill in frontend development. We break down difficult concepts into easy-to-understand terms, allowing you to naturally master everything from the basic principles of React to practical application through hands-on learning. By addressing the common pain points where beginners often get stuck and providing project-based practice, we help you grow into a confident React developer.

Learn how to reduce marketing risks through AI and efficiently execute the entire process, from branding and personalized marketing to content creation. From the basics of prompt engineering to practical application, we present essential AI utilization methods for marketing professionals.

You will systematically learn the principles and practical applications of the latest generative AI technologies, from ChatGPT to image and video generation AI and no-code tools. Through seven core topics, including prompt engineering, Copilot utilization, and AI extensions, you can maximize work efficiency and develop creative problem-solving skills.

This course does not simply list concepts. 👉 It explains the entire flow of IT systems based on "how a service actually operates." User Request → Server Processing → Data Storage → Result Return Web/App → API → DB → Cloud 👉 Centered around this flow, it connects where, why, and how each technology is used.

The real story of an AI-native company run by GolbinHacker, the 1st place winner of Kakao AI TOP 100 and author of the bestseller "The Best Prompt Engineering Lecture." It explores how just two developers build and operate a service, along with the new competencies developers and organizations need in the AI era through real-world cases.

We will create various design outputs such as logos, product photos, mockups, banners, wedding snaps, invitations, POPs, menus, and product detail pages using ChatGPT Images 2.0. This is a practice-oriented course where you will learn how to write prompts to achieve your desired results and master template structures that can be used repeatedly.

Together with Professor Soon-chil Lee, South Korea's leading authority on quantum computing, you will systematically learn everything from the core principles of quantum technology to its business impact. Through the basic concepts of quantum mechanics, the operating principles of quantum computers, and industrial application cases, you will complete your quantum literacy to preemptively understand future technological changes and establish strategies.

The Gemini agent that works across Google Drive! Put the finishing touches on your Google AI workflow with overwhelming productivity.

How long will you keep struggling with repetitive daily research and document writing? I, too, was an ordinary office worker who worked overtime every day trying to find key insights amidst an overflow of information. However, after integrating Gemini 3 into my workflow, I experienced a significant increase in work speed. Boost your productivity by utilizing Gemini in your tasks.

This is an introductory course where you learn the core concepts of Claude Code through a 3D office analogy. From hiring a single robot in an empty office, giving it a brain and a heart, equipping it with tools, permissions, and memory, to eventually having multiple robots work together as a team—each concept unfolds as an office scene. You will master every concept by interacting with the digital course materials and complete your learning through hands-on practice on your own computer.

An easy-to-understand lecture by the author of [AI Leadership], a management scholar with a background in program development and a creative organization HR expert

Feeling overwhelmed by where to start with AI auditing? AI has moved beyond a mere technology trend and is rapidly expanding into corporate decision-making, workflow automation, customer service, recruitment, security, and risk management. However, compared to the speed of AI adoption, not many people systematically understand questions like: "Is the AI being properly controlled?", "Can we trust the AI's judgment?", or "What risks could arise from the data, models, and operational processes?" In particular, those working in IT auditing, security, internal control, and project management often face these concerns: - How does AI auditing differ from traditional IT auditing? - Is it enough to just look at the code for an AI model, or must we examine the data and training process as well? - How do AI governance, risk, bias, explainability, MLOps, and incident response connect to one another? - Where should I start to understand the concepts covered in AI auditing certification courses like AAIA from a practical perspective? This course was created specifically to resolve this sense of uncertainty. For about 20 years, I have gained experience in IT service planning, development, PM, collaboration platform operation, groupware construction, chatbot service planning, and security and audit-related tasks. I have firsthand experience in how systems are planned, developed, and operated in actual organizations, and how failures, changes, security, and user requirements are interconnected. Furthermore, I have synthesized the perspectives of IT auditing and AI auditing through CISA and AAIA study programs. In this course, rather than diving deep into complex AI technology through math or development, I focus on the core concepts that auditors and IT practitioners must understand. We will examine AI systems by breaking them down into the flow of data, models, operations, security, governance, risk, and audit procedures, and summarize what controls and checkpoints are required at each stage. Through this course, students will understand that AI auditing is not simply "evaluating AI," but rather the task of inspecting governance, risk, and control systems to ensure that AI is used safely and responsibly within an organization. This course is suitable for: - Those new to AI auditing. - Those in IT auditing or security who want to expand into the AI domain. - Those who want to organize AI governance and risk from a practical perspective. - Those who want to grasp the overall concepts before starting AI audit-related studies such as AAIA. Upon completing the course, you will be able to answer the following questions yourself: - What components make up an AI system? - What should an AI auditor check during the data, model, and operation stages? - Why are AI governance and Responsible AI important? - How are AI risk, bias, explainability, privacy, and security connected? - What perspectives and evidence should be included in an AI audit report? In the rapidly changing era of AI, the ability to manage and inspect technology to make it trustworthy is just as important as the ability to use it well. This course is an introductory program for those who want to understand the big picture of AI auditing step-by-step from the beginning. Let's build the first standard for looking at IT and AI from an auditing perspective together.

In an era of explosive data growth and crucial real-time processing, edge computing has established itself as an essential technology, no longer an option. This course is designed to systematically teach everything, from the core concepts of edge computing to deployment strategies for its application in real business environments. Through this course, students will firmly solidify the fundamental principles of edge computing and acquire practical knowledge and know-how applicable to real-world tasks and projects. Take the most certain first step towards becoming an edge computing expert, a core technology in the future IT environment!

AI Tech DNA Series: Core Principles of Computer Basics from an AI Perspective is an introductory course designed to help you easily understand the fundamental computer concepts necessary for the AI era. By explaining basic principles such as CPU, memory, storage, networks, and data structures through real-life analogies and an AI-focused lens, it builds the solid foundational strength needed to advance into Python, AI, security, and the cloud.

All lectures have been newly updated for June 2026, reflecting all the latest content. 5-Hour All-in-One Course → Apply directly to work with only the most essential services Practical AI Specialist Course → Step-by-step learning from sign-up to in-depth application Curated Essential AI for Work → Focus on core tools you actually use instead of 100 unused lectures Perfect Integration with Books → AI learning that can be utilized for a lifetime even without a textbook

1. A practice-oriented lecture designed to help you pass the AICE Associate, Korea's only nationally recognized AI certification. 2. Learn to the level of performing data analysis and AI modeling based on Python.

You have likely seen many misleading lectures about monetizing AI music. Yes, AI music monetization is possible. It is simply not difficult enough to justify paying expensive tuition, nor is it a way to make easy money. This is an action-oriented course for those who are interested in AI music monetization but feel lost on where to start. Based on my personal experience of creating AI music, organizing albums, distributing tracks, and utilizing YouTube and TikTok, I have structured the workflow—from music generation and album planning to file preparation, distribution, and monetization setup—so you can follow along from the very beginning. This course does not guarantee profits; rather, it is designed to help you experience the entire process of releasing AI music and preparing for monetization from start to finish.

Systematically learn the core concepts and operating principles of Imitation Learning and VLA (Vision-Language-Action) technologies, which serve as the foundation for Physical AI. Understand the mechanisms through which Physical AI interacts with the real world through actual case study analysis.

There may be people who have never taken my lecture, but no one has taken it only once. After teaching in person for so long, I have finally had the opportunity to create this online course. Since the commercialization of AI, I have produced and researched countless pieces of AI content. Based on that knowledge and experience, I have built a logical philosophy of my own and organized it into concepts that are easy for anyone to understand. For those who have been generating AI images without considering the underlying concepts, I will instill a proper foundation in you. Once you take this course, you will be able to create any AI image in the future. Have you never created an AI image before? That’s perfectly fine. You don't need any prior experience in AI image generation. By simply learning and practicing through this lecture, you can become an expert in AI content creation.

From asset management using proptech to AI-based intelligent logistics and transportation system analysis, and even profitable smart home models, we provide practical know-how to design real business revenue models using technology as a tool.

Delegate the pressure of overflowing financial data and reports to an AI agent. From corporate analysis to report automation, an overwhelming workflow for financial experts that changes the game of practical business!

['Thought Architect' Roadmap for Translating Technical Truth into Business Value] 1. Introduction: Analysis of Constraints in Transferring Technical Truth to Business Value A significant bottleneck frequently observed across corporate sectors and engineering sites (R&D) is the phenomenon where innovative achievements, backed by massive resources and research capabilities, are discarded because they fail to overcome the 'communication threshold.' This is judged to stem from information asymmetry: a situation where management does not sufficiently perceive the depth of deep-tech, and technical personnel fail to appropriately utilize business language. This masterclass redefines the 'text-based communication competency' of engineers and scientists not as a mere administrative act of recording, but as part of a precise 'Engineering Design' process. Through this, we aim to present a mechanism by which an engineer's technical insights are transformed beyond simple records into core assets that drive the organization's strategic decision-making. 2. [Diagnosis] Analysis of Three Major Cognitive Defects Hindering Technical Communication ① Disconnection of Information Transfer due to the Curse of Knowledge This phenomenon occurs when experts become immersed in their own advanced level of knowledge and overlook the cognitive background of the information recipient. Consequently, reports centered on obscure formulas and technical acronyms are repeated, which is highly likely to result in structural losses such as loss of contact with decision-makers, delays in project approval, and failure in resource allocation. ② Value Loss due to Lack of Logical Architecture and Data Fragmentation By regarding document preparation as a simple post-hoc administrative procedure, errors of listing information without systematic design are frequently observed. These structural defects significantly damage the value of R&D achievements during the delivery process, tending to lead not only to the undervaluation of an individual engineer's capabilities but also to the loss of tangible and intangible assets for the entire organization. ③ Technical Reliability Crisis due to Deepening AI Dependency If generative AI, introduced to improve productivity, causes hallucinations without understanding the technical context, 'technical reliability'—the core value of engineering—can be seriously undermined. Utilizing AI without an accompanying logical verification system is highly likely to act as a potential system risk rather than a work efficiency tool. 3. [Prescription] Strategic Communication System for the Thought Architect ① Engineering Design of Thought for Unstructured Information A process of structuring abstract experimental data and hypotheses based on engineering system design principles is required. Bottom Line Up Front (BLUF): By placing core values and recommendations at the forefront of the document, we aim for an information structure optimized so that management can perform rapid and accurate decision-making (capital investment, mass production approval, etc.). Mutually Exclusive, Collectively Exhaustive (MECE): By adhering to principles that prevent logical overlap and omission, we ensure the logical completeness of the report by designing a seamless flow of thought. ② Global Standard Compliance and Quality Assurance Objectivity and integrity of data must be secured by internalizing standard protocols recognized by the global scientific community and global corporations. Standard Technical Reporting Structure (IMRaD): Maintain the consistency and reliability of the engineering narrative through a rigorous formal structure leading from Introduction, Methods, Results, to Discussion. 5 Principles of Sentence Quality (5C): By applying Correctness, Clarity, Conciseness, Consistency, and Completeness as quality control filters, we establish a Plain Language system that even non-experts can understand immediately. ③ S.E.E.D Prompt Architecture for Securing AI Command To operate AI not as a simple ghostwriting tool but as an assistant performing logical operations, a dedicated interface design must be involved. S.E.E.D Framework: Precisely control the quality of AI outputs by systematically structuring and inputting Situation, Expectation, Engineering Structure, and Data. Human-in-the-Loop: Establish a protocol where humans perform verification as the final approver to block the possibility of AI errors, thereby firmly maintaining technical authority. 4. [Execution] Strategies for Securing Cognitive Sovereignty and Workflow Optimization Communication competency acts as a core mechanism for preserving an engineer's cognitive functions beyond mere technical means. Responsibility-based Sandwich Workflow: Humans must perform context design (Top Bun) and final verification (Bottom Bun), delegating only the intermediate data processing (Meat) stage to AI to promote the activation of the human-unique Executive Control Network (ECN). RQTDW Learning Protocol for Knowledge Internalization: Apply the five stages of Read, Question, Think (facing contradictions), Discuss (virtual discussion), and Write to practical work to avoid simple acceptance of information and actively internalize knowledge. SIFT Model-based Precision Fact-Checking: Filter AI hallucinations and maintain technical precision through the process of Source (checking the origin), Investigate (understanding context), Find (cross-checking), and Trace. 5. Conclusion: Transition from Technical Expert to Engineering Leader The era of practitioners who simply perform given technical tasks is coming to an end. The ability to translate and communicate complex and difficult technical truths into a 'language of value' acceptable to organizations and society can be defined as a core survival strategy and a noble calling for modern engineers. Text communication is the Final Interface that projects an engineer's intellectual capacity to the outside world, beyond a simple act of recording. Through this masterclass, we expect you to prove your technical value and emerge as a powerful 'Engineering Leader' who drives organizational change. This system, which integrates 40 years of engineering insight, will become a strategic asset that completes your status as a professional.

This course is ideal for those who want to focus on theory and context rather than practice, aiming to organize their knowledge of deep learning in depth and grasp the big picture. It makes the mathematical and statistical foundations of deep learning easy to understand and provides intuitive interpretations of key modern models—such as AutoEncoder, GAN, Transformer, and AlphaGo—from a developer's perspective.